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The Stable Diffusion model supports the ability to generate new images from scratch through the use of a text prompt describing elements to be included or omitted from the output. [8] Existing images can be re-drawn by the model to incorporate new elements described by a text prompt (a process known as "guided image synthesis" [ 49 ] ) through ...
Stable Diffusion, prompt a photograph of an astronaut riding a horse Producing high-quality visual art is a prominent application of generative AI. [ 65 ] Generative AI systems trained on sets of images with text captions include Imagen , DALL-E , Midjourney , Adobe Firefly , FLUX.1 , Stable Diffusion and others (see Artificial intelligence art ...
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
Example of prompt engineering for text-to-image generation, with Fooocus. In 2022, text-to-image models like DALL-E 2, Stable Diffusion, and Midjourney were released to the public. [47] These models take text prompts as input and use them to generate AI-generated images.
Midjourney is a generative artificial intelligence program and service created and hosted by the San Francisco-based independent research lab Midjourney, Inc. Midjourney generates images from natural language descriptions, called prompts, similar to OpenAI's DALL-E and Stability AI's Stable Diffusion. [1] [2] It is one of the technologies of ...
Instead of an autoregressive Transformer, DALL-E 2 uses a diffusion model conditioned on CLIP image embeddings, which, during inference, are generated from CLIP text embeddings by a prior model. [22] This is the same architecture as that of Stable Diffusion, released a few months later.
Image and video generators like DALL-E (2021), Stable Diffusion 3 (2024), [45] and Sora (2024), use Transformers to analyse input data (like text prompts) by breaking it down into "tokens" and then calculating the relevance between each token using self-attention, which helps the model understand the context and relationships within the data.
Various AI models, such as Llama 2, Mistral or Stable Diffusion, have been made open-weight, [312] [313] meaning that their architecture and trained parameters (the "weights") are publicly available. Open-weight models can be freely fine-tuned , which allows companies to specialize them with their own data and for their own use-case. [ 314 ]